9f6fa2654c3fbe1764cd53a97189ede9b0ebdb92,tests/test_hypersphere.py,TestHypersphere,test_sample_von_mises_fisher,#TestHypersphere#,638

Before Change

        mean_estimate = sum_points / gs.linalg.norm(sum_points)
        expected = mean
        result = mean_estimate
        self.assertTrue(
            gs.allclose(result, expected, atol=MEAN_ESTIMATION_TOL)
        )
        // check concentration parameter for dispersed distribution
        kappa = 1.
        points = sphere.random_von_mises_fisher(kappa, n_points)
        sum_points = gs.sum(points, axis=0)

After Change

        // check mean value for concentrated distribution for different mean
        kappa = 10000000
        mean = sphere.random_uniform()
        points = sphere.random_von_mises_fisher(
            mu=mean, kappa=kappa, n_samples=n_points)
        sum_points = gs.sum(points, axis=0)
        result = sum_points / gs.linalg.norm(sum_points)
        expected = mean
        self.assertAllClose(result, expected, atol=MEAN_ESTIMATION_TOL)

        // check concentration parameter for dispersed distribution

Instances